This study analyzed the impact of vegetables’ contract farming on the household’s income using data collected from 423 smallholder vegetable farmers from four districts of the East Shewa zone, central rift valley of Ethiopia. The study combines both quantitative and qualitative data obtained from desk review, an in-depth household interview, and focus group discussions. The propensity score-matching technique was employed for data analysis due to lack of baseline data and non-randomness of participation in contract farming. First, a probit regression model was used to estimate the propensity for matching participants and non-participants. Then, their incomes were compared. Results show that contract farming has a significant positive effect on the incomes of participating households. Given the vegetable production opportunities available in the study area, it is important to address the challenges of vegetable producers to benefit from contract farming and increase their incomes.

Purpose: The main objective of this study was to investigate the influence of contract farming on the technical efficiency of dairy farmers in urban and peri-urban areas, specifically in Nekemte City, Ethiopia. Design/Methodology/Approach: The research design employed to obtain the data was a cross-sectional study. For data analysis, both primary and secondary sources of information were gathered. A semi-structured questionnaire was used to collect primary data. A simple random sampling technique was followed to select 181 sample dairy farm producers in urban and peri-urban areas of Nekemte city. The data analysis methods that were employed included descriptive analysis, Cobb-Douglas stochastic frontier analysis, and the propensity score matching technique. Findings: According to the Cobb-Douglas stochastic frontier production function results, the most significant input in milk production is fodder, which has the biggest coefficient (= 0.353). The sum of the coefficients of all inputs is 0.512, and dairy farmers in the study area have been operating at decreasing returns to scale. The result of logistic regressions showed that the owner or manager's age, education, and experience are important factors that influence their decision to participate in urban dairy contract farming. The results of the propensity score matching technique showed that dairy farmers' technical efficiency increased by 0.150, or 21.52%, because of contract farming. Conclusion: The results of the study highlight that contract farming helps dairy farmers in urban and peri-urban areas become more technically efficient. Research Implications: The result of the study can serve as an input for policy formulation and serve as a stepping stone for other researchers.

In the last decades, Ethiopia has been one of the fastest growing non-oil producing countries in the world. Along with the economic growth, inflation has been rising. Therefore, the main objective of this study was to identify the major macroeconomic factors affecting inflation in Ethiopia for the year 1981 - 2020. Secondary data were collected from World development indicators database. Both econometrics and descriptive statistics were used for data analysis. The findings of the descriptive result indicated that for forty years the mean official exchange rate was 10.13birr/dollar with standard deviation of 8.6Birr/dollar. The mean inflation rate for Ethiopia was 9.44% with a minimum of -9.81% and a maximum value of 44.39%. Growth of GDP was 5.91% with standard deviation of 6.45%. In order to show long run and short run relationship between variables, vector error correction regression model was applied. Before estimation, stationery test was conducted using dickey fuller test. Inflation rate and growth of GDP were stationary at level while exchange rate and unemployment rate were non-stationary. Therefore, vector error correction model was justifiable. The result of vector error correction model confirmed that there is a significant relationship between devaluation of exchange rate and inflation. Therefore, in order to control inflationary pressure appropriate polices must be designed which compromises unemployment, economic growth and exchange rate regimes.

The major of this study was to estimate the impact of Adoption of Small-Scale Irrigation in Dugda district. Data were collected from both primary and secondary data sources. Primary data was collected from 384 household heads in four kebeles of the district using structured questionnaire. Descriptive, logit and propensity score matching techniques were used for data analysis. The study finding from the propensity score matching technique revealed that the incomes of adopters of small scale irrigation were increased by 37,696.06ETB per annum. This calls for strengthening the available irrigation facilities and expansion of irrigation sector in the study area.

Maize is a key crop for food security and rural livelihoods in Ethiopia, yet little is known about the factors that affect how efficiently smallholder farmers produce it in Guto Gidda District, Oromia. This study addresses this gap by examining the determinants of technical efficiency among maize farmers. Data were collected from 423 households using a structured questionnaire, and a two-stage sampling process was followed to select three kebeles (Loko, Uke Badiya, and Aleltu) based on their maize production potential. The data were analyzed using descriptive statistics, Stochastic Frontier Analysis (SFA), and a two-limit Tobit regression model. Results from the SFA showed an average technical efficiency of 0.804, with scores ranging from 0.002 to 0.989, suggesting that farmers could, on average, improve output by nearly 20% using existing inputs through better resource management. The two-limit Tobit regression indicated that household head age, education, access to credit, engagement in non-/off-farm activities, training, and adoption of improved maize varieties significantly increased technical efficiency. In contrast, larger landholdings were associated with lower efficiency, likely due to fragmented plots, poor soil quality, and labor constraints. These findings suggest that policies and programs should focus on improving access to credit, promoting off-farm income opportunities, providing targeted training, encouraging adoption of improved seeds, and supporting better land management. Addressing these factors can help farmers produce maize more efficiently, contributing to food security and sustainable livelihoods in the district.